Current models of spoken word recognition have been predominantly based on studies of Indo-European languages. As a result, little is known about the recognition processes involved in the perception of tonal languages (e.g., Mandarin Chinese), and the role of lexical tone in speech perception. One view is that tonal languages are processed phonologically through individual segments, while another view is that they are processed lexically as a whole. Moreover, a recent study claimed to be the first to discover an early phonological processing stage in Mandarin (Huang et al., 2014). There seems to be a lack of investigations concerning tonal languages, as no clear conclusions have been made about the nature of tonal processes, or a model of spoken word recognition that best incorporates lexical tone. The current study addressed these issues by presenting 18 native Mandarin speakers with aural sentences with medial target words, which either matched or mismatched the preceding visually presented sentences with medial target words (e.g, 家 /jia1/ "home"). Violation conditions involved target words that differed in the following ways: tone violation, where only the tone was different (e.g., 价 /jia4/ "price"), onset violation, where only the onset was different (e.g., 虾 /xia1/ "shrimp"), and syllable violation, where both the tone and the onset were different (e.g., 糖 /tang2/ "candy"). We did not find evidence for an early phonological processing stage in Mandarin. Instead, our findings indicate that Mandarin syllables are processed incrementally through phonological segments and that lexical tone is strongly associated with semantic access. These results are discussed with respect to modifications for v existing models in spoken word recognition to incorporate the processes involved with tonal language recognition. vi Acknowledgements This thesis would not have been possible without the efforts of many. I am deeply indebted to my principal supervisor, Dr. John F. Connolly for his invaluable guidance and thoughtful perspectives on various aspects of this research. My appreciation for his contributions is beyond my words. I am truly grateful for my second supervisor, Dr. Anna L. Moro, for her warm support and valued insight on the formation of my research question and stimuli. My Mandarin instructor, Ms. Jun Wu (吴老师), played a significant role in creating sentential contexts for my target words, and I am incredibly thankful for her help. I specifically thank Daniel Schmidtke and Dr. Elisabet Service for their involvement with my statistical analyses. I would also like to thank Christine Zhang, Jing Wen, and Lisa Lin for recording my stimuli, and Kai Fan for reviewing my stimuli for native accuracy.I would like to extend my gratitude to the Language Memory and Brain Lab (LMBLab) for dedicating their time and effort in assisting me with collecting data and running participants. Of the LMBLab, Rober Boshra deserves a special mention for his much-appreciated assistance in programming my experiment and sincere reassurances.Fu...